Reducing the amount of data stored in a sequence of data blocks by combining deduplication and compression

ABSTRACT

The described technology is generally directed towards reducing the amount of data stored in a sequence of data blocks by combining deduplication and compression. According to an embodiment, a system can comprise a memory that can store computer executable components, and a processor that can execute the components stored in the memory. The components can comprise a data block identifier that can identify, for a sequence of data blocks, a first data block that corresponds to a first data, resulting in a first identified data block, and a deduplication component that can identify a second data block that corresponds to the first data, resulting in a second identified data block, wherein the deduplication component can replace the second identified data block with a key value corresponding to the first identified data block. Further, a compression component can compress the first identified data block, resulting in a compressed data block.

TECHNICAL FIELD

The subject application generally relates to data storage andcommunications, and, for example, to adaptive deduplication andcompression of data, and related embodiments.

BACKGROUND

Modern data systems can require the storage and communication ofincreasing amounts of data. Reducing the size of this data can reduceboth the cost and time associated with storing and communicating thedata.

In some circumstances, removing duplicate data can be used to reduce thesize of the data, but this operation does not result in size reductionwhen the data does not have a lot of duplicates. Alternatively, datacompression can reduce the size of non-duplicate data, but using thisapproach can cause deduplication to either not be performed, orperformed with substantial overhead.

SUMMARY

This Summary is provided to introduce a selection of representativeconcepts in a simplified form that are further described below in theDetailed Description. This Summary is not intended to identify keyfeatures or essential features of the claimed subject matter, nor is itintended to be used in any way that would limit the scope of the claimedsubject matter.

According to an embodiment, a system can comprise a memory that storescomputer executable components and a processor that can execute thecomputer executable components stored in the memory. The computerexecutable components can comprise a data block identifier that canidentify, for a sequence of data blocks, a first data block thatcorresponds to a first data, resulting in a first identified data block,and a deduplication component that can identify a second data block thatcorresponds to the first data, resulting in a second identified datablock, wherein the deduplication component can replace the secondidentified data block with a key value corresponding to the firstidentified data block. Further, a compression component can compress thefirst identified data block, resulting in a compressed data block.

According to another embodiment, a computer-implemented method cancomprise receiving, by a first device comprising a processor, from asecond device, a sequence of elements, wherein respective ones of thesequence of elements comprise blocks of data. The method can furthercomprise decompressing, by the first device, a compressed block of dataof a first element of the sequence of elements, resulting in a firstblock of data comprised in the first element. The method can furthercomprise storing, by the first device, a copy of the first block of dataas a second block of data comprised in a second element, wherein thestoring the first block of data is based on a key value referencing thefirst element.

According to another embodiment, a computer program product is provided.The computer program product can comprise machine-readable storagemedium comprising executable instructions that, when executed by aprocessor, can facilitate performance of operations comprisingidentifying a first data block in the sequence of data blocks thatcorresponds to a first data, resulting in a first identified data block.The operations can further comprise identifying a second data block inthe sequence of data blocks that corresponds to the first data,resulting in a second identified data block, wherein the secondidentified data block is replaced by a key value corresponding to thefirst identified data block. The operations can further comprisecompressing the first identified data block, resulting in a compresseddata block.

BRIEF DESCRIPTION OF THE DRAWINGS

The technology described herein is illustrated by way of example and notlimited in the accompanying figures in which like reference numeralsindicate similar elements, and in which:

FIG. 1 illustrates a block diagram of an example, non-limiting systemthat can facilitate reducing the amount of data stored in a sequence ofdata blocks by combining deduplication and compression, in accordancewith various aspects and implementations of the subject disclosure.

FIG. 2 illustrates an implementation of an example, non-limiting systemthat can facilitate reducing the amount of data stored in a sequence ofdata blocks by combining deduplication and compression, in accordancewith one or more embodiments described herein.

FIGS. 3-4 respectively provide a flow diagram and a sample sequence ofelements to describe different embodiments discussed herein.

FIG. 5 depicts a flow diagram of a non-limiting, example process bywhich data can be recovered after the deduplication and compressionprocesses described above, in accordance with one or more embodiments.

FIG. 6 depicts a non-limiting sample of computer code that can configurethe operation of one or more embodiments.

FIG. 7 illustrates an example flow diagram for a method that canfacilitate reducing the amount of data stored in a sequence of datablocks by combining deduplication and compression, in accordance withone or more embodiments.

FIG. 8 is a flow diagram representing example operations of systemcomprising data block identifier, deduplication component, andcompression component, in accordance with one or more embodiments.

FIG. 9 depicts an example schematic block diagram of a computingenvironment with which the disclosed subject matter can interact, inaccordance with one or more embodiments.

FIG. 10 illustrates an example block diagram of a computing systemoperable to execute the disclosed systems and methods in accordance withvarious aspects and implementations of the subject disclosure.

DETAILED DESCRIPTION

Various aspects described herein are generally directed towardsfacilitating reducing the amount of data stored in a sequence of datablocks by combining deduplication and compression, in accordance withone or more embodiments. As will be understood, the implementation(s)described herein are non-limiting examples, and variations to thetechnology can be implemented.

Reference throughout this specification to “one embodiment,” “one ormore embodiments,” “an embodiment,” “one implementation,” “animplementation,” etc. means that a particular feature, structure, orcharacteristic described in connection with theembodiment/implementation is included in at least oneembodiment/implementation. Thus, the appearances of such a phrase “inone embodiment,” “in an implementation,” etc. in various placesthroughout this specification are not necessarily all referring to thesame embodiment/implementation. Furthermore, the particular features,structures, or characteristics may be combined in any suitable manner inone or more embodiments/implementations.

The computer processing systems, computer-implemented methods, apparatusand/or computer program products described herein employ hardware and/orsoftware to solve problems that are highly technical in nature (e.g.,reducing the amount of data stored in a sequence of data blocks bycombining deduplication and compression), that are not abstract andcannot be performed as a set of mental acts by a human. For example, ahuman, or even a plurality of humans, cannot efficiently integrate datacompression (which generally cannot be performed manually by a human)and deduplication, with the same level of accuracy and/or efficiency asthe various embodiments described herein.

Aspects of the subject disclosure will now be described more fullyhereinafter with reference to the accompanying drawings in which examplecomponents, graphs and operations are shown. In the followingdescription, for purposes of explanation, numerous specific details areset forth in order to provide a thorough understanding of the variousembodiments. However, the subject disclosure may be embodied in manydifferent forms and should not be construed as limited to the examplesset forth herein.

FIG. 1 illustrates a block diagram of an example, non-limiting system100 that can facilitate reducing the amount of data stored in a sequenceof data blocks by combining deduplication and compression, in accordancewith various aspects and implementations of the subject disclosure.

As depicted, host device 110A can be coupled to another host device 110Bby employing network 140. In some embodiments, processor 130 cancomprise one or more of a central processing unit, multi-core processor,microprocessor, dual microprocessors, microcontroller, System on a Chip(SOC), array processor, vector processor, and/or another type ofprocessor. Further examples of processor 130 are described below withreference to processing unit 1014 and FIG. 10. Such examples can beemployed with any embodiments of the subject disclosure.

As discussed further below with FIG. 10, in some embodiments, memory 118can comprise volatile memory (e.g., random access memory (RAM), staticRAM (SRAM), dynamic RAM (DRAM), etc.) and/or non-volatile memory (e.g.,read only memory (ROM), programmable ROM (PROM), electricallyprogrammable ROM (EPROM), electrically erasable programmable ROM(EEPROM), etc.) that can employ one or more memory architectures.Further examples of memory 118 are described below with reference tosystem memory 1016 and FIG. 10. Such examples of memory 118 can beemployed to implement any embodiments of the subject disclosure.

According to multiple embodiments, processor 130 can comprise one ormore types of processors and/or electronic circuitry that can implementone or more computer and/or machine readable, writable, and/orexecutable components and/or instructions that can be stored on memory118. For example, processor 130 can perform various operations that canbe specified by such computer and/or machine readable, writable, and/orexecutable components and/or instructions including, but not limited to,logic, control, input/output (I/O), arithmetic, and/or the like.

In one or more embodiments, in an example approach to performing theoperations above, processor 130 can execute computer-executablecomponents 120, including data block identifier 122, deduplicationcomponent 124, restoring component 125, compression component 126,decompression component 127, and data structure component 128.

Data store 160 can provide persistent storage to one or moreembodiments, including by employing the use of data structure 165.Generally speaking, in some circumstances, data structures can be usedto organize data so as to facilitate the performance of differentoperations, e.g., manipulation and searching. Because one or moreembodiments described herein can use both of these operationsextensively, some implementations described herein can use a datastructure.

For example, a binary search tree can be used to facilitate rapidsearching, with every element in the tree is a structure which can holdboth a key value and a data value, and with elements of the binarysearch tree being represented by assigned key values. These datastructures can be useful for implementation of some embodimentsdescribed herein because they can facilitate fast lookup, addition andremoval of items. It should be appreciated however, that this example isnot intended to be limiting, and data structures can be used toimplement one or more embodiments. The above example is non-limiting,and it should be noted that other approaches to manipulating andsearching operations can be used to implement one or more embodiments,including, but not limited to, directly modifying and performing linearsearches on, an array.

FIG. 2 illustrates an implementation of an example, non-limiting system200 that can facilitate reducing the amount of data stored in a sequenceof data blocks by combining deduplication and compression in a dataprotection system, in accordance with one or more embodiments describedherein. Repetitive description of like elements and/or processesemployed in respective embodiments is omitted for sake of brevity.

An example system that can benefit in some circumstances from the use ofone or more embodiments, is a data protection system. In differentimplementations. Data protection systems can copy host data from primarystorage in computing device to secondary storage. For data protectionsystems that can utilize remote data replication, the systems can copydata from one geographical location to a remote secondary storage devicelocated on a different location, e.g., for disaster recovery and faulttolerance, e.g., the SRDF System provided by DELL EMC, discussed above.

This figure depicts an example implementation of one or more embodimentswhere some of the features of example host devices 110A-B of FIG. 1 areembodied in data replication devices 210A-C. Data replication device210A can be coupled to other data replication devices (e.g., datareplication devices 210B-C) by employing both local area network (LAN)140 and wide area network (WAN) 145. As used herein, WAN 245 can be anetwork that can connect computer devices over a wide geographical area,e.g., a municipal network, national network, and global network. Use ofWAN 245 to connect data replication device 210A to data replicationdevice 210C can add additional potential shortcomings compared toconnections employing LAN 240. For example, problems that include, butare not limited to customer limited network bandwidth pipes, round triptime (RTT) latency, packet drops, packet timeouts, and re-transmits, canalso occur more frequently with the use of WAN 245.

Data protection systems can benefit from the data reduction of one ormore embodiments at least because these systems can store large amountsof data (e.g., by employing data store 260) and can communicate largeamounts of data over network connections (e.g., by employing LAN 240 andWAN 245). Data reduction can improve both the cost and performance ofboth of these operations.

FIGS. 3-4 respectively provide a flow diagram 300 and a sample sequenceof elements 400 to describe different embodiments discussed herein.Repetitive description of like elements and/or processes employed inrespective embodiments is omitted for sake of brevity.

At block 310 the data to be processed is identified. One or moreembodiments can divide blocks of data into blocks of a particular size.This selected block size can have a relationship to some part of thesystem for which the processes described herein are performed. Forexample, in data replication system discussed with FIG. 2 above, data isbeing reduced before communication to another host, where is can berecovered back to its unreduced size. In this application the selecteddata block size can be based on data sizes associated with the physicalaspects of the system, e.g., data store 160 as a storage device in theSymmetrix System discussed above. Thus, because in this example, storagedevices are divided into tracks, tracks are divided into data blocks,these data blocks can be used as the information unit upon which one ormore embodiments can operate.

As depicted in FIG. 4, furthering this connection between one or moreembodiments and system hardware, one or more embodiments discussedherein operate on sequences of a particular number of elements (e.g.,data blocks 415), and in the example data replication system discussedabove, for 128 kb track 420, there are 256 data blocks 415 of 512 bytes.Thus, returning to block 310 in FIG. 3, in this example, track 420 of aphysical drive is identified for processing. It is important to notethat the above example is non-limiting and alternative implementationscan have more or fewer data blocks, of different sizes, that can also beunrelated to physical storage devices.

At block 320, the manipulation (e.g., duplicate removal and compression)of the identified data blocks can be enabled, e.g., by buffering thedata using different approaches. As discussed above, because theprocessing performed by one or more embodiments can involve searching, adata structure designed for searching can be used (e.g., binary searchtrees), but any approach to manipulating the identified data blocks canbe used, without departing from the spirit of the embodiments describedherein.

In this example, for simplicity, FIG. 4 provides a simple, 256 elementdata structure 410A-C with a bottom row providing a position in the datablock, e.g., which 512 b data block is referenced, e.g., data block B4corresponding to the 4th 512 b block. As discussed in additional detailbelow, in this example, the top row can store either a data value (e.g.,the 512 b of data in the 4th position), a compressed version of the datavalue, or a key value (e.g., one byte) that can correspond to anotherposition in the data block. Thus, in the initial collection of data410A, data blocks B1-B256 contain capital letters A-G, as shorthand for512 b of uncompressed unique data.

At block 330, one or more embodiments can traverse the sequence of datablocks, e.g., B1-B256 of 410A, to compare the elements with previouselements processed. In one or more embodiments, traversal begins at B1,and the value (e.g., 512 b) stored at this block can be compared to allother blocks that have been processed (e.g., none), and if no match withany previous element 337, data block B1 can be tagged as a uniqueelement 338. Tagging can occur in different ways, including but notlimited to, in metadata of the data block, or in an external datasource, e.g., a list of unique key values. At discussed further below,the unique value in block B1 can be compressed by one or moreembodiments, after deduplication.

Continuing with this example, data block B2 is also tagged as unique,based on the process described with block B1 above. As depicted in datablocks 410B, when one or more embodiments processes block B3 accordingto the block 330 of FIG. 3, because the “A” value has been processedpreviously with block B1, there is a match with previously taggedelements 335. Thus, in block 337, the “A” value in block B3 can bereplaced with a key value 430 that references block B1, as the firstinstance of the “A” value processed. In an implementation, because thereare 256 data blocks, one byte of data can be used to reference any ofthe data blocks in 430B, and thus deduplication has reduced the size ofthe data by 511 bytes. As depicted, data blocks B6-B7 are also processedin this way, e.g., having data values stored in these blocks replacedwith a reference to data block B1.

Once traversal of the sequence of elements is completed 340, at block350, the elements identified (e.g., in block 340) as being unique can becompressed. Thus, as depicted in 410C, data block B1 contains acompressed value 440 with a lower-case “a” to indicate a compressed “A”value. Also having unique values, data blocks B2, B4, B5, B8, B9, andB256 are also compressed.

As discussed further with FIG. 6 below, the sequence of elements, aswell as the elements individually, can have metadata that describedifferent characteristics of the system. For example, after thecompletion of block 350 above, metadata header information for elementscan be updated to store information about the current state of the data,e.g., which blocks contain key value references to unique values (e.g.,were subject to deduplication) and which elements are compressed, uniqueinstances. As discussed with FIG. 5 below, this information can be usedfor a data recovery process.

FIG. 5 depicts a flow diagram 500 of a non-limiting, example process bywhich data can be recovered after the deduplication and compressionprocesses described above, in accordance with one or more embodiments.Repetitive description of like elements and/or processes employed inrespective embodiments is omitted for sake of brevity.

In block 510, similar to block 320 discussed above, manipulation of thedata to be restored can be enabled using any approach, such asbuffering. In block 520, the sequence of elements (e.g., data blocks410C) can be traversed, and decompression can be performed on thecompressed elements, e.g., based on a metadata indication that a datablock contains compressed data. Thus, as shown in the transition fromdata blocks 410C to 410B, the lower case letters representing compressed512 b blocks are returned to uppercase.

In block 530, the sequence of data blocks 410B can be traversed again,and the key values associated with the remaining data blocks can bereplaced with the, now uncompressed, data stored in these blocks. Thus,as depicted in the transition from data blocks 410B to 410A, the keyvalue of 1 stored in memory block B3 can reference the “A” stored inmemory block B1, and this value can replace the key value for memoryblock B3, as well as memory blocks B6-B7 by the same process. After thisdistribution of the unique values to the data blocks with key values,the original data can have been restored 540.

It should be noted that, in this non-limiting example, the decompressionstep occurs before the restoration of the removed duplicate data, e.g.,the decompressed data is copied to the destination data blocks. In oneor more embodiments, this can be performed for different reasons,including, but not limited to, the overhead saved by only having todecompress the compressed data once.

FIG. 6 depicts a non-limiting sample of computer code 600 that canconfigure the operation of one or more embodiments to facilitatereducing the amount of data stored in a sequence of data blocks bycombining deduplication and compression. Repetitive description of likeelements and/or processes employed in respective embodiments is omittedfor sake of brevity.

It should be noted that while the computer code depicted in FIG. 6 isexample code from a computer language with custom data types, anycomputer programming language can have code that performs similarfunctions. Commands 610A-B are new data type commands, and list outmembers of each data type, including for 610A, instances of the 610Bdata type. Command 610B defines a data type 680 that describesinformation about a particular data block, having a member 660 thatincludes a variable to hold the length of the data after compression,and member 670 that includes an operation code that can specify whetherthe data is in its original form, a compressed form, or a pointer toanother instance of the data, e.g., in this example, 0, 1, and 2,respectively. Command 610A creates a data type 650 for the entiresequence of data blocks, and includes a member 620 to define the numberof data blocks (e.g., 256 as with FIG. 4 above) and a member 630 forchunk size, e.g., the size of each data block element, e.g., 512 bdescribed above. This data type can also provide an array of the 610Bcommand data type, e.g., one for each of the data blocks.

FIG. 7 illustrates an example flow diagram for a method 700 that canfacilitate reducing the amount of data stored in a sequence of datablocks by combining deduplication and compression, in accordance withone or more embodiments. For purposes of brevity, description of likeelements and/or processes employed in other embodiments is omitted.

At element 702, method 700 can comprise receiving, by a first device(e.g., host device 110A) comprising a processor 130, from a seconddevice (e.g., host device 110B), a sequence of elements (e.g., datablocks 410C), wherein respective ones of the sequence of elementscomprise blocks of data (e.g., B1-B256 of data blocks 410C).

At element 704, method 700 can comprise decompressing, by the firstdevice (e.g., host device 110A), a compressed block (e.g., data block410C) of data of a first element (e.g., block B1 of data blocks 410C) ofthe sequence of elements, resulting in a first block of data (e.g.,lower case “a” decompressed to uppercase “A” in transition from datablocks 410C to 410B) comprised in the first element.

At element 706, method 700 can comprise storing, by the first device(e.g., host device 110A), a copy of the first block of data (e.g., theuppercase “A” in block B1) as a second block (e.g., storing “A” in blockB3 of data blocks 410A) of data comprised in a second element, whereinthe storing the first block of data (e.g., the transition between datablocks 410B and 410A) is based on a key value (e.g., the key value of 1in block B3 of data blocks 410B) referencing the first element (e.g.,block B1).

FIG. 8 is a flow diagram representing example operations of systemcomprising data block identifier 122, deduplication component 124, andcompression component 126, in accordance with one or more embodiments.For purposes of brevity, description of like elements and/or processesemployed in other embodiments is omitted.

Data block identifier 122 can be configured 802 to identify a first datablock (e.g., data block B1 in data blocks 410A) in the sequence of datablocks that corresponds to a first data (e.g., “A”), resulting in afirst identified data block.

Deduplication component 124 can be configured to identify a second datablock (e.g., block B3 in data blocks 410B) in the sequence of datablocks that corresponds to the first data (e.g., block B3 also containsan “A”), resulting in a second identified data block, wherein thededuplication component replaces the second identified data block (e.g.,the transition between data blocks 410A and 410B) with a key valuecorresponding to the first identified data block (e.g., block B3 of datablocks 410B contains a key value that references block B1).

Compression component 126 can be configured to compress the firstidentified data block, resulting in a compressed data block (e.g., thetransition between data blocks 410B and 410C, with the uppercase “A”being compressed to a lowercase “a” in block B1).

FIG. 9 is a schematic block diagram of a system 900 with which thedisclosed subject matter can interact. The system 900 comprises one ormore remote component(s) 910. The remote component(s) 910 can behardware and/or software (e.g., threads, processes, computing devices).In some embodiments, remote component(s) 910 can be a distributedcomputer system, connected to a local automatic scaling component and/orprograms that use the resources of a distributed computer system, viacommunication framework 940. Communication framework 940 can comprisewired network devices, wireless network devices, mobile devices,wearable devices, radio access network devices, gateway devices,femtocell devices, servers, etc.

The system 900 also comprises one or more local component(s) 920. Thelocal component(s) 920 can be hardware and/or software (e.g., threads,processes, computing devices).

One possible communication between a remote component(s) 910 and a localcomponent(s) 920 can be in the form of a data packet adapted to betransmitted between two or more computer processes. Another possiblecommunication between a remote component(s) 910 and a local component(s)920 can be in the form of circuit-switched data adapted to betransmitted between two or more computer processes in radio time slots.The system 900 comprises a communication framework 940 that can beemployed to facilitate communications between the remote component(s)910 and the local component(s) 920, and can comprise an air interface,e.g., Uu interface of a UMTS network, via a long-term evolution (LTE)network, etc. Remote component(s) 910 can be operably connected to oneor more remote data store(s) 950, such as a hard drive, solid statedrive, SIM card, device memory, etc., that can be employed to storeinformation on the remote component(s) 910 side of communicationframework 940. Similarly, local component(s) 920 can be operablyconnected to one or more local data store(s) 930, that can be employedto store information on the local component(s) 920 side of communicationframework 940.

In order to provide a context for the various aspects of the disclosedsubject matter, FIG. 8, and the following discussion, are intended toprovide a brief, general description of a suitable environment in whichthe various aspects of the disclosed subject matter can be implemented.While the subject matter has been described above in the general contextof computer-executable instructions of a computer program that runs on acomputer and/or computers, those skilled in the art will recognize thatthe disclosed subject matter also can be implemented in combination withother program modules. Generally, program modules comprise routines,programs, components, data structures, etc. that performs particulartasks and/or implement particular abstract data types.

In the subject specification, terms such as “store,” “storage,” “datastore,” “data storage,” “database,” and substantially any otherinformation storage component relevant to operation and functionality ofa component, refer to “memory components,” or entities embodied in a“memory” or components comprising the memory. It is noted that thememory components described herein can be either volatile memory ornonvolatile memory, or can comprise both volatile and nonvolatilememory, by way of illustration, and not limitation, volatile memory 1020(see below), non-volatile memory 1022 (see below), disk storage 1024(see below), and memory storage, e.g., local data store(s) 930 andremote data store(s) 950, see below. Further, nonvolatile memory can beincluded in read only memory, programmable read only memory,electrically programmable read only memory, electrically erasable readonly memory, or flash memory. Volatile memory can comprise random accessmemory, which acts as external cache memory. By way of illustration andnot limitation, random access memory is available in many forms such assynchronous random access memory, dynamic random access memory,synchronous dynamic random access memory, double data rate synchronousdynamic random access memory, enhanced synchronous dynamic random accessmemory, SynchLink dynamic random access memory, and direct Rambus randomaccess memory. Additionally, the disclosed memory components of systemsor methods herein are intended to comprise, without being limited tocomprising, these and any other suitable types of memory.

Moreover, it is noted that the disclosed subject matter can be practicedwith other computer system configurations, comprising single-processoror multiprocessor computer systems, mini-computing devices, mainframecomputers, as well as personal computers, hand-held computing devices(e.g., personal digital assistant, phone, watch, tablet computers,netbook computers, . . . ), microprocessor-based or programmableconsumer or industrial electronics, and the like. The illustratedaspects can also be practiced in distributed computing environmentswhere tasks are performed by remote processing devices that are linkedthrough a communications network; however, some if not all aspects ofthe subject disclosure can be practiced on stand-alone computers. In adistributed computing environment, program modules can be located inboth local and remote memory storage devices.

FIG. 10 illustrates a block diagram of a computing system 1000 operableto execute the disclosed systems and methods in accordance with one ormore embodiments/implementations described herein. Computer 1012 cancomprise a processing unit 1014, a system memory 1016, and a system bus1018. System bus 1018 couples system components comprising, but notlimited to, system memory 1016 to processing unit 1014. Processing unit1014 can be any of various available processors. Dual microprocessorsand other multiprocessor architectures also can be employed asprocessing unit 1014.

System bus 1018 can be any of several types of bus structure(s)comprising a memory bus or a memory controller, a peripheral bus or anexternal bus, and/or a local bus using any variety of available busarchitectures comprising, but not limited to, industrial standardarchitecture, micro-channel architecture, extended industrial standardarchitecture, intelligent drive electronics, video electronics standardsassociation local bus, peripheral component interconnect, card bus,universal serial bus, advanced graphics port, personal computer memorycard international association bus, Firewire (Institute of Electricaland Electronics Engineers 1394), and small computer systems interface.

System memory 1016 can comprise volatile memory 1020 and non-volatilememory 1022. A basic input/output system, containing routines totransfer information between elements within computer 1012, such asduring start-up, can be stored in non-volatile memory 1022. By way ofillustration, and not limitation, non-volatile memory 1022 can compriseread only memory, programmable read only memory, electricallyprogrammable read only memory, electrically erasable read only memory,or flash memory. Volatile memory 1020 comprises read only memory, whichacts as external cache memory. By way of illustration and notlimitation, read only memory is available in many forms such assynchronous random access memory, dynamic read only memory, synchronousdynamic read only memory, double data rate synchronous dynamic read onlymemory, enhanced synchronous dynamic read only memory, SynchLink dynamicread only memory, Rambus direct read only memory, direct Rambus dynamicread only memory, and Rambus dynamic read only memory.

Computer 1012 can also comprise removable/non-removable,volatile/non-volatile computer storage media. FIG. 10 illustrates, forexample, disk storage 1024. Disk storage 1024 comprises, but is notlimited to, devices like a magnetic disk drive, floppy disk drive, tapedrive, flash memory card, or memory stick. In addition, disk storage1024 can comprise storage media separately or in combination with otherstorage media comprising, but not limited to, an optical disk drive suchas a compact disk read only memory device, compact disk recordabledrive, compact disk rewritable drive or a digital versatile disk readonly memory. To facilitate connection of the disk storage 1024 to systembus 1018, a removable or non-removable interface is typically used, suchas interface 1026.

Computing devices typically comprise a variety of media, which cancomprise computer-readable storage media or communications media, whichtwo terms are used herein differently from one another as follows.

Computer-readable storage media can be any available storage media thatcan be accessed by the computer and comprises both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structureddata, or unstructured data. Computer-readable storage media cancomprise, but are not limited to, read only memory, programmable readonly memory, electrically programmable read only memory, electricallyerasable read only memory, flash memory or other memory technology,compact disk read only memory, digital versatile disk or other opticaldisk storage, magnetic cassettes, magnetic tape, magnetic disk storageor other magnetic storage devices, or other tangible media which can beused to store desired information. In this regard, the term “tangible”herein as may be applied to storage, memory or computer-readable media,is to be understood to exclude only propagating intangible signals perse as a modifier and does not relinquish coverage of all standardstorage, memory or computer-readable media that are not only propagatingintangible signals per se. In an aspect, tangible media can comprisenon-transitory media wherein the term “non-transitory” herein as may beapplied to storage, memory or computer-readable media, is to beunderstood to exclude only propagating transitory signals per se as amodifier and does not relinquish coverage of all standard storage,memory or computer-readable media that are not only propagatingtransitory signals per se. Computer-readable storage media can beaccessed by one or more local or remote computing devices, e.g., viaaccess requests, queries or other data retrieval protocols, for avariety of operations with respect to the information stored by themedium. As such, for example, a computer-readable medium can compriseexecutable instructions stored thereon that, in response to execution,can cause a system comprising a processor to perform operations,comprising determining a mapped cluster schema, altering the mappedcluster schema until a rule is satisfied, allocating storage spaceaccording to the mapped cluster schema, and enabling a data operationcorresponding to the allocated storage space, as disclosed herein.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and comprises any informationdelivery or transport media. The term “modulated data signal” or signalsrefers to a signal that has one or more of its characteristics set orchanged in such a manner as to encode information in one or moresignals. By way of example, and not limitation, communication mediacomprise wired media, such as a wired network or direct-wiredconnection, and wireless media such as acoustic, RF, infrared and otherwireless media.

It can be noted that FIG. 10 describes software that acts as anintermediary between users and computer resources described in asuitable operating environment, e.g., computing system 1000. Suchsoftware comprises an operating system 1028. Operating system 1028,which can be stored on disk storage 1024, acts to control and allocateresources of computer 1012. System applications 1030 take advantage ofthe management of resources by operating system 1028 through programmodules 1032 and program data 1034 stored either in system memory 1016or on disk storage 1024. It is to be noted that the disclosed subjectmatter can be implemented with various operating systems or combinationsof operating systems.

A user can enter commands or information into computer 1012 throughinput device(s) 1036. In some embodiments, a user interface can allowentry of user preference information, etc., and can be embodied in atouch sensitive display panel, a mouse/pointer input to a graphical userinterface (GUI), a command line controlled interface, etc., allowing auser to interact with computer 1012. Input devices 1036 comprise, butare not limited to, a pointing device such as a mouse, trackball,stylus, touch pad, keyboard, microphone, joystick, game pad, satellitedish, scanner, TV tuner card, digital camera, digital video camera, webcamera, cell phone, smartphone, tablet computer, etc. These and otherinput devices connect to processing unit 1014 through system bus 1018 byway of interface port(s) 1038. Interface port(s) 1038 comprise, forexample, a serial port, a parallel port, a game port, a universal serialbus, an infrared port, a Bluetooth port, an IP port, or a logical portassociated with a wireless service, etc. Output device(s) 1040 use someof the same type of ports as input device(s) 1036.

Thus, for example, a universal serial bus port can be used to provideinput to computer 1012 and to output information from computer 1012 toan output device 1040. Output adapter 1042 is provided to illustratethat there are some output devices 1040 like monitors, speakers, andprinters, among other output devices 1040, which use special adapters.Output adapters 1042 comprise, by way of illustration and notlimitation, video and sound cards that provide means of connectionbetween output device 1040 and system bus 1018. It should be noted thatother devices and/or systems of devices provide both input and outputcapabilities such as remote computer(s) 1044.

Computer 1012 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1044. Remote computer(s) 1044 can be a personal computer, a server, arouter, a network PC, cloud storage, a cloud service, code executing ina cloud computing environment, a workstation, a microprocessor-basedappliance, a peer device, or other common network node and the like, andtypically comprises many or all of the elements described relative tocomputer 1012. A cloud computing environment, the cloud, or othersimilar terms can refer to computing that can share processing resourcesand data to one or more computer and/or other device(s) on an as neededbasis to enable access to a shared pool of configurable computingresources that can be provisioned and released readily. Cloud computingand storage solutions can store and/or process data in third-party datacenters which can leverage an economy of scale and can view accessingcomputing resources via a cloud service in a manner similar to asubscribing to an electric utility to access electrical energy, atelephone utility to access telephonic services, etc.

For purposes of brevity, only a memory storage device 1046 isillustrated with remote computer(s) 1044. Remote computer(s) 1044 islogically connected to computer 1012 through a network interface 1048and then physically connected by way of communication connection 1050.Network interface 1048 encompasses wire and/or wireless communicationnetworks such as local area networks and wide area networks. Local areanetwork technologies comprise fiber distributed data interface, copperdistributed data interface, Ethernet, Token Ring and the like. Wide areanetwork technologies comprise, but are not limited to, point-to-pointlinks, circuit-switching networks like integrated services digitalnetworks and variations thereon, packet switching networks, and digitalsubscriber lines. As noted below, wireless technologies may be used inaddition to or in place of the foregoing.

Communication connection(s) 1050 refer(s) to hardware/software employedto connect network interface 1048 to system bus 1018. Whilecommunication connection 1050 is shown for illustrative clarity insidecomputer 1012, it can also be external to computer 1012. Thehardware/software for connection to network interface 1048 can comprise,for example, internal and external technologies such as modems,comprising regular telephone grade modems, cable modems and digitalsubscriber line modems, integrated services digital network adapters,and Ethernet cards.

The above description of illustrated embodiments of the subjectdisclosure, comprising what is described in the Abstract, is notintended to be exhaustive or to limit the disclosed embodiments to theprecise forms disclosed. While specific embodiments and examples aredescribed herein for illustrative purposes, various modifications arepossible that are considered within the scope of such embodiments andexamples, as those skilled in the relevant art can recognize.

In this regard, while the disclosed subject matter has been described inconnection with various embodiments and corresponding Figures, whereapplicable, it is to be understood that other similar embodiments can beused or modifications and additions can be made to the describedembodiments for performing the same, similar, alternative, or substitutefunction of the disclosed subject matter without deviating therefrom.Therefore, the disclosed subject matter should not be limited to anysingle embodiment described herein, but rather should be construed inbreadth and scope in accordance with the appended claims below.

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit, a digital signalprocessor, a field programmable gate array, a programmable logiccontroller, a complex programmable logic device, a discrete gate ortransistor logic, discrete hardware components, or any combinationthereof designed to perform the functions described herein. Processorscan exploit nano-scale architectures such as, but not limited to,molecular and quantum-dot based transistors, switches and gates, inorder to optimize space usage or enhance performance of user equipment.A processor may also be implemented as a combination of computingprocessing units.

As used in this application, the terms “component,” “system,”“platform,” “layer,” “selector,” “interface,” and the like are intendedto refer to a computer-related entity or an entity related to anoperational apparatus with one or more specific functionalities, whereinthe entity can be either hardware, a combination of hardware andsoftware, software, or software in execution. As an example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration and not limitation, both anapplication running on a server and the server can be a component. Oneor more components may reside within a process and/or thread ofexecution and a component may be localized on one computer and/ordistributed between two or more computers. In addition, these componentscan execute from various computer readable media having various datastructures stored thereon. The components may communicate via localand/or remote processes such as in accordance with a signal having oneor more data packets (e.g., data from one component interacting withanother component in a local system, distributed system, and/or across anetwork such as the Internet with other systems via the signal). Asanother example, a component can be an apparatus with specificfunctionality provided by mechanical parts operated by electric orelectronic circuitry, which is operated by a software or a firmwareapplication executed by a processor, wherein the processor can beinternal or external to the apparatus and executes at least a part ofthe software or firmware application. As yet another example, acomponent can be an apparatus that provides specific functionalitythrough electronic components without mechanical parts, the electroniccomponents can comprise a processor therein to execute software orfirmware that confers at least in part the functionality of theelectronic components.

In addition, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances.

While the invention is susceptible to various modifications andalternative constructions, certain illustrated implementations thereofare shown in the drawings and have been described above in detail. Itshould be understood, however, that there is no intention to limit theinvention to the specific forms disclosed, but on the contrary, theintention is to cover all modifications, alternative constructions, andequivalents falling within the spirit and scope of the invention.

In addition to the various implementations described herein, it is to beunderstood that other similar implementations can be used ormodifications and additions can be made to the describedimplementation(s) for performing the same or equivalent function of thecorresponding implementation(s) without deviating therefrom. Stillfurther, multiple processing chips or multiple devices can share theperformance of one or more functions described herein, and similarly,storage can be effected across a plurality of devices. Accordingly, theinvention is not to be limited to any single implementation, but ratheris to be construed in breadth, spirit and scope in accordance with theappended claims.

What is claimed is:
 1. A system, comprising: a memory that storescomputer executable components; and a processor that executes thecomputer executable components stored in the memory, wherein thecomputer executable components comprise: a data block identifier toidentify, for a sequence of data blocks, a first data block in thesequence of data blocks that corresponds to first data, resulting in afirst identified data block; a deduplication component to identify, forthe sequence of data blocks, a second data block in the sequence of datablocks that corresponds to the first data, resulting in a secondidentified data block, wherein the deduplication component replaces thesecond identified data block with a key value corresponding to the firstidentified data block; and a compression component to compress the firstidentified data block, resulting in a compressed data block.
 2. Thesystem of claim 1, wherein the system comprises a data protectionsystem, and wherein the sequence of data blocks corresponds to data tobe replicated based on the data protection system.
 3. The system ofclaim 1, wherein the compression component further replaces the firstidentified data block with the compressed data block.
 4. The system ofclaim 1, wherein the data block identifier further tags the firstidentified data block to be compressed by the compression component, andwherein the compression component compresses the first identified datablock based on the tagging of the first identified data block by thedata block identifier.
 5. The system of claim 1, wherein the firstidentified data block comprises a header portion that comprisesmetadata, wherein the data block identifier tags the first identifieddata block by updating the metadata, resulting in updated metadata, andwherein the compression component compresses the first identified datablock based on the updated metadata.
 6. The system of claim 1, whereinthe computer executable components further comprise: a decompressioncomponent to decompress the compressed data block resulting in adecompressed data block, wherein the decompression component furtherreplaces the compressed data block with the decompressed data block; anda restoring component to identify, for the sequence of data blocks, thekey value and, based on the key value, replace the key value with a copyof the decompressed data block.
 7. The system of claim 1, wherein thecomputer executable components further comprise: a search tree componentto manipulate a search tree data structure comprising the sequence ofdata blocks, wherein: the data block identifier identifies the firstdata block based on a first search of the search tree data structure,the deduplication component identifies the second data block based on asecond search of the search tree data structure, and replaces, in thesearch tree data structure, the second identified data block with thekey value, and the compression component compresses the first identifieddata block in the search tree data structure, resulting in thecompressed data block being stored in the search tree data structure. 8.The system of claim 7, wherein, based on a first search of the searchtree data structure, the data block identifier further tags the firstidentified data block to be compressed by the compression component, andwherein the compression component compresses the first identified datablock based on the tagging of the first identified data block by thedata block identifier.
 9. The system of claim 7, wherein the search treedata structure comprises a binary search tree data structure.
 10. Amethod, comprising: receiving, by a first device comprising a processor,from a second device, a sequence of elements, wherein respective ones ofthe sequence of elements comprise blocks of data; decompressing, by thefirst device, a compressed block of data of a first element of thesequence of elements, resulting in a first block of data comprised inthe first element; and storing, by the first device, a copy of the firstblock of data as a second block of data comprised in a second element,wherein the storing the first block of data is based on a key valuereferencing the first element.
 11. The method of claim 10, wherein therespective ones of the sequence of elements further comprise metadatathat describes contents of the blocks of data comprised in therespective ones of the sequence of elements.
 12. The method of claim 11,wherein the metadata comprised in the first element of the sequence ofelements comprises a first indicator that the first element comprisescompressed data, and wherein the decompressing the compressed block ofdata is based on the first indicator.
 13. The method of claim 12,wherein the metadata comprised in the first element comprises a valuecorresponding to a length of the compressed block of data.
 14. Themethod of claim 11, wherein the metadata comprised in the first elementof the sequence of elements comprises a second indicator that the secondelement comprises the key value referencing the first element, andwherein the storing the copy of the first block of data is based on thesecond indicator.
 15. The method of claim 10, further comprising,copying data corresponding to the sequence of elements to a track of astorage device.
 16. The method of claim 10, wherein the first device andthe second device are comprised in a data protection system and thesequence of elements corresponds to data replicated by the first deviceto the second device based on the data protection system.
 17. The methodof claim 10, wherein the sequence of elements comprises metadata thatdescribes aspects of the sequence of elements.
 18. A non-transitorymachine-readable storage medium comprising executable instructions that,when executed by a processor, facilitate performance of operations, theoperations comprising: identifying a first data block in a sequence ofdata blocks that corresponds to a first data, resulting in a firstidentified data block; identifying a second data block in the sequenceof data blocks that corresponds to the first data, resulting in a secondidentified data block, wherein the second identified data block isreplaced by a key value corresponding to the first identified datablock; and compressing the first identified data block, resulting in acompressed data block.
 19. The non-transitory machine-readable medium ofclaim 18, wherein the operations further comprise tagging the firstidentified data block to be compressed, and wherein the compressing thefirst identified data block is based on the tagging of the firstidentified data block.
 20. The non-transitory machine-readable medium ofclaim 19, wherein the first identified data block comprises a headerportion that comprises metadata, wherein the tagging the firstidentified data block comprises updating the metadata, resulting inupdated metadata, and wherein the compressing the first identified datablock is based on the updated metadata.